324 citations · 1k across the 27 of their papers we have counts for
34 papers
Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation
Rishi Sonthalia, Raj Rao Nadakuditi
We introduce a novel regularization scheme for autoencoders based on matricial free energy. Our approach defines a differentiable loss function in terms of the singular values of t…
Smooth optimization using global and local low-rank regularizers
Rodrigo A. Lobos, Javier Salazar Cavazos, Raj Rao Nadakuditi +1
Many inverse problems and signal processing problems involve low-rank regularizers based on the nuclear norm. Commonly, proximal gradient methods (PGM) are adopted to solve this ty…
Detection thresholds in very sparse matrix completion
Charles Bordenave, Simon Coste, Raj Rao Nadakuditi
Let be a rectangular matrix of size and be the random matrix where each entry of is multiplied by an independent -Bernoulli random variable with…
Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting
Arvind Prasadan, Raj Rao Nadakuditi, Debashis Paul
Singular value decomposition (SVD) based principal component analysis (PCA) breaks down in the high-dimensional and limited sample size regime below a certain critical eigen-SNR th…
Free Component Analysis: Theory, Algorithms & Applications
Hao Wu, Raj Rao Nadakuditi
We describe a method for unmixing mixtures of freely independent random variables in a manner analogous to the independent component analysis (ICA) based method for unmixing indepe…
Time Series Source Separation using Dynamic Mode Decomposition
Arvind Prasadan, Raj Rao Nadakuditi
The Dynamic Mode Decomposition (DMD) extracted dynamic modes are the non-orthogonal eigenvectors of the matrix that best approximates the one-step temporal evolution of the multiva…